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 #  3ab = c3*3d df <- 0:9 %>% {tidyr::crossing(a = ., b = ., c = ., d = .)} %>% filter(300 + a * 10 + b == (c * 10 + 3) * (30 + d)) df 

 ops <- c('*', '/', '+', '-') #      df <- tidyr::crossing(op1 = ops, op2 = ops, op3 = ops, op4 = ops) %>% #        mutate(data = glue::glue("7 {op1} (7 {op2} 7 {op3} 7) {op4} 7"), expr = rlang::parse_exprs(data)) %>% mutate(res = purrr::map_dbl(expr, rlang::eval_bare)) %>% arrange(res) %>% filter(res == 8) print(tbl_df(df), n = 20) 

 #  100   4,      99 #    tidyr::crossing(d1 = 0:9, d2 = 0:9) %>% #   ,   4 filter(d1 == 4 | d2 == 4) %>% arrange(d1, d2) 

 #   : abc df <- tidyr::crossing(b = 0:9, c = 0:9) %>% #    9     mutate(delta = (900 + 10*b + c) - (100*b + 10*c + 9)) %>% filter(between(delta, 200, 230)) df 

 numbers::primeFactors(2520) 

 # https://joftius.wordpress.com/2015/10/19/finding-multiple-roots-of-univariate-functions-in-r/ f <- function(x) {x * (x+1) * (x+2) * (x+3) * (x+4) - 2520} rootSolve::uniroot.all(f, c(0, 2520)) 

 eq <- "x * (x+1) * (x+2) * (x+3) * (x+4) - 2520" yacas(glue("Simplify({eq})")) #            rts <- base::polyroot(c(-2520, 24, 50, 35, 10, 1)) #     n-1 #     # http://www.johnmyleswhite.com/notebook/2009/12/18/using-complex-numbers-in-r/ Re(rts[abs(Im(rts)) < 1^-10]) 

 tibble(num = 5430 + 0:9, mod = mod(num, 4)) %>% arrange(mod, num) 

 2*(1/3*(1/4*60)) 60 %>% {./4} %>% {./3} %>% {.*2} 

 #       2  ,   #    ,    =  sum(1:12) / 2 #    for (i in 1:12){ res <- cumsum(i:12) print(glue(" : {i},  : {glue_collapse(res, ', ')}")) val <- which(res == 39) if(! identical(val, integer(0))){ print(glue("  [{i}; {val + i - 1}]")) } } 

 library(tidyverse) library(stringi) #   "an_bn_cn". c --    df <- c(1, 2, 3, 4, 5) %>% {tidyr::crossing(an = ., bn = ., cn = .)} %>% #    mutate(comb = purrr::pmap(., c)) %>% #     mutate(val = stri_join(an, bn, cn)) %>% #      # 314 -  1  filter(stri_detect_regex(val, "3[^1][^4]|[^3]1[^4]|[^3][^1]4")) %>% # 124 -  1  filter(stri_detect_regex(val, "1[^2][^4]|[^1]2[^4]|[^1][^2]4")) %>% # 523 -  1  filter(stri_detect_regex(val, "5[^2][^3]|[^5]2[^3]|[^5][^2]3")) %>% #      filter(purrr::map_int(comb, n_distinct) == 3) %>% #      (1   1 ) filter(purrr::map(comb, ~length(base::intersect(.x, c(3, 1, 4)))) == 2) %>% filter(purrr::map(comb, ~length(base::intersect(.x, c(1, 2, 4)))) == 2) %>% filter(purrr::map(comb, ~length(base::intersect(.x, c(5, 2, 3)))) == 2) df 

 library(tidyverse) library(stringi) df <- c(1, 2, 3, 4, 5) %>% tidyr::crossing(d3 = ., d2 = ., d1 = .) %>% #    mutate(comb = purrr::pmap(., c)) %>% #     mutate(val = stri_join(d3, d2, d1)) %>% #      # 543 -- 1 ; 0  filter(stri_detect_regex(val, "5..|.4.|..3")) %>% # 235 -- 1 ; 0  filter(stri_detect_regex(val, "2..|.3.|..5")) %>% #      filter(purrr::map_int(comb, n_distinct) == 3) %>% #      filter(purrr::map(comb, ~length(base::intersect(.x, c(5, 4, 3)))) == 1) %>% filter(purrr::map(comb, ~length(base::intersect(.x, c(2, 3, 5)))) == 1) df 

 #      ,    10.  : 3, 3, 3, 1 library(arrangements) library(foreach) #   : # 1 2 3 4 # 5 6 7 8 # 9 10 11 12 # 13 14 15 16 cmb <- arrangements::combinations(1:16, k = 10, replace = FALSE) pryr::object_size(cmb) #   ,   ,   .  icomb <- icombinations(1:16, k = 10, replace = FALSE) foreach(x = icomb, .combine=c) %do% { # x -    ,    "" #       #  isOdd <- function(x, set){ #   length(base::intersect(x, set)) %% 2 == 1 } isEven <- function(x, set){ #   length(base::intersect(x, set)) %% 2 == 0 } col_flag <- all( isOdd(x, c(1, 5, 9, 13)), isOdd(x, c(2, 6, 10, 14)), isOdd(x, c(3, 7, 11, 15)), isOdd(x, c(4, 8, 12, 16)) ) row_flag <- all( isEven(x, c(1, 2, 3, 4)), isEven(x, c(5, 6, 7, 8)), isEven(x, c(9, 10, 11, 12)), isEven(x, c(13, 14, 15, 16)) ) if(col_flag && row_flag) print(x) } 

 #      ,    10.  : 3, 3, 3, 1 library(tidyverse) library(magrittr) library(arrangements) library(foreach) #   : # 1 2 3 4 # 5 6 7 8 # 9 10 11 12 # 13 14 15 16 #   ,   ,   .  icomb <- icombinations(1:16, k = 10, replace = FALSE) df <- foreach(x = icomb, .combine = rbind) %do% { # x -    ,    "" #       #   v <- rep(0, 16) #   ,   # browser() v[x] <- 1 m <- matrix(v, nrow = 4, ncol = 4, byrow = TRUE) #  :      , #        if (all(colSums(m) %% 2 == 1) && all(rowSums(m) %% 2 == 0)) x else NULL } df %<>% as_tibble(.name_repair = "minimal") #       v <- rep(0, 16) #   ,   v[purrr::flatten_int(df[5, ])] <- 1 matrix(v, nrow = 4, ncol = 4, byrow = TRUE) 

 #     # https://stackoverflow.com/questions/44918645/split-a-string-into-character-efficiently lset <- unlist(base::strsplit("", split = "", fixed = TRUE)) #       ,      lset <- c("", "1", "", "2") # library(permutations) df <- tidyr::crossing(p1 = lset, p2 = lset, p3 = lset, p4 = lset) ff <- function(...){ vals <- rlang::list2(...) # browser() n_distinct(unlist(vals)) } df %>% # mutate(u = purrr::pmap_int(., ~n_distinct(.x))) mutate(u = purrr::pmap_int(., ff)) %>% filter(u == 4) %>% select(-u) %>% #      mutate(s = purrr::pmap_chr(., stri_join)) %>% mutate_at(vars(s), stri_replace_all_regex, pattern = "(\\d+)", replacement = "") %>% distinct(s) %>% #     filter(!stri_detect_fixed(s, "")) 

 #   ,     366 %/% 7 #   .         366 %% 7 

 df <- tidyr::crossing(a = 0:2, b = 0:2, c = 0:2) %>% mutate(total = a + b + c) %>% mutate(a_lie = (b != 2) + (total != 2), b_lie = (c != 2) + (total != 3), c_lie = (a != 2) + (total != 4)) %>% filter(a_lie == a, b_lie == b, c_lie == c) df